Grid computing services, utility-based data centers, and other types of resource-on-demand systems are becomingly increasingly popular as a means for efficiently and cost-effectively taking advantage of computer resources to meet the computing demands of users. However, managing these resource-on-demand systems is a difficult task that conventional network management software is not equipped to handle.
Many management tasks are performed manually, which tends to be time consuming and costly. For example, selecting computer resources from a pool of resources to assign to a particular user's computing demands is typically performed manually. The monitoring of the pool of resources may be performed using conventional management tools. However, the decision of which resources to select for a user's computing demands or whether to reassign resources after initially selecting resources is performed by a system administrator. In addition, current resource-on-demand systems may not efficiently utilize available resources from the resource pool. For example, in many systems, resources remain idle and unused if not assigned to a particular user, even if assigning the idle resources may result in increased efficiency for the user's applications.